Computational Scientist; Mass Spectrometry

Charter:

Be a founding member of a team building the first accurate AI systems for drug toxicity prediction to replace lab and animal experiments.

At the highest level, we only want to hire people who deeply inspire us and relentlessly push us to be better. They must level up the entire team, bringing significant energy and a sense of awe. High agency is critical: they see what’s important and they do it. Doing is the key but it should be guided by great taste for what truly matters.

We’re looking for folks doing those niche hobbies and activities, the ones that might not make sense at first glance, but eventually reveal profound depth and passion when you dive in with them. These individuals act with intentionality or whimsical naivety like an immigrant in a new country, a performer trying to break out, or someone teaching themselves to code or garden.

There must be a deep curiosity for all facets of Axiom, an ambition fueling their exploration of what we do. They want to do something here, to dive in headfirst, but they know they need to learn more, so they search with an insatiable hunger. They need to be cracked, technically excellent, obsessive masters of their craft. They’re irrational; they could work in big tech, but they know it will not satisfy them.

They want the pain of doing something brutally hard along with the riches and glory when it finally works.

We’re building AI systems for drug safety and toxicity assessment. Drug toxicity causes about half of drug program failures and by tackling it we can help drug discovery teams across the industry bring new medicines to patients far faster. To understand toxicity in the liver we need to get a clearer picture of its biochemistry: mass spectrometry is a critical tool in this endeavour.

We’re looking for a mass spectrometry bioinformatician who is excited to apply their expertise to help eliminate animal testing and prevent clinical failures. You’ll work closely with our biology, machine learning, engineering, biology and lab teams to design and debug assays, develop machine learning models, and generate actionable biological insights. This role is ideal for someone who thrives in a fast-moving environment, wants ownership over major scientific contributions, and is motivated by solving foundational challenges at the intersection of chemistry, AI, and human health.

• Analyzing different kinds of biological mass spectrometry data (mostly LC-MS/MS) with existing software tools (like mzmine or openms)
• Extending these tools with new features and building new software from the ground up
• Scaling workflows to process large amounts of data for human and AI consumption

• Developing computational workflows for untargeted LC-MS/MS analysis in metabolomics
• Applying these tools to solve biological problems

• Computational proteomics
• Computational lipidomics
• DIA (Data Independent Acquisition)
• Machine learning
• Liver metabolism
• Reactive metabolite
• Designing high throughput LC-MS/MS experiments
• Wet lab LC-MS/MS
• NMR data analysis
• Data visualization